Systems

2472 KiB

Open AccessArticle

Ship Routing with Pickup and Delivery for a Maritime Oil Transportation System: MIP Model and Heuristics

by Vinícius P. Rodrigues, Reinaldo Morabito, Denise Yamashita, Bruno J. V. Da Silva and Paulo C. Ribas

Systems 2016, 4(3), 31; https://doi.org/10.3390/systems4030031 - 21 Sep 2016

Cited by 18 | Viewed by 8612

Abstract

This paper examines a ship routing problem with pickup and delivery and time windows for maritime oil transportation, motivated by the production and logistics activities of an oil company operating in the Brazilian coast. The transportation costs from offshore platforms to coastal terminals [...] Read more.

This paper examines a ship routing problem with pickup and delivery and time windows for maritime oil transportation, motivated by the production and logistics activities of an oil company operating in the Brazilian coast. The transportation costs from offshore platforms to coastal terminals are an important issue in the search for operational excellence in the oil industry, involving operations that demand agile and effective decision support systems. This paper presents an optimization approach to address this problem, based on a mixed integer programming (MIP) model and a novel and exploratory application of two tailor-made MIP heuristics, based on relax-and-fix and time decomposition procedures. The model minimizes fuel costs of a heterogeneous fleet of oil tankers and costs related to freighting contracts. The model also considers company-specific constraints for offshore oil transportation. Computational experiments based on the mathematical models and the related MIP heuristics are presented for a set of real data provided by the company, which confirm the potential of optimization-based methods to find good solutions for problems of moderate sizes. Full article

► Show Figures

Figure 1

3101 KiB

Open AccessArticle

Feedback-Based Eco-Design for Integrating the Recency, Frequency, and Monetary Value of Eco-Efficiency into Sustainability Management

by Rui Yang Chen

Systems 2016, 4(3), 30; https://doi.org/10.3390/systems4030030 - 14 Sep 2016

Cited by 5 | Viewed by 6836

Abstract

Customer feedback is used to understand customer requirements. Early design phases require the consideration of items including manufacturing, the environment, and sustainability management. Therefore, it is crucial that eco-efficiency is taken into account in the early design phases. Traditionally, eco-efficiency is considered only [...] Read more.

Customer feedback is used to understand customer requirements. Early design phases require the consideration of items including manufacturing, the environment, and sustainability management. Therefore, it is crucial that eco-efficiency is taken into account in the early design phases. Traditionally, eco-efficiency is considered only in terms of eco-design issues, not customer requirements based on business values such as Recency, Frequency, and Monetary (RFM) value. In the meantime, integrating innovation from eco-design is one important aspect. Here, I propose that customer feedback-based eco-efficiency and TRIZ-based innovation can be considered in early eco-design based on the RFM value for sustainability management. The analytic hierarchy process (AHP) and fuzzy-based AHP were integrated to explore the relative weights of RFM variables for business value evaluation. The innovative method of the paper is using a TRIZ contradiction matrix associated with engineering parameters for eco-design. The experimental study has been carried out, and it meets the forecasting business value for green product usage. The business value was used as the decision-making factor in order to evaluate both environmental and marketing performance. Full article

(This article belongs to the Special Issue Product, Process, System Design Review Methods and Tools)

► Show Figures

Figure 1

3819 KiB

Open AccessArticle

Model of the Russian Federation Construction Innovation System: An Integrated Participatory Systems Approach

by Emiliya Suprun, Oz Sahin, Rodney A. Stewart and Kriengsak Panuwatwanich

Systems 2016, 4(3), 29; https://doi.org/10.3390/systems4030029 - 16 Aug 2016

Cited by 17 | Viewed by 10029

Abstract

This research integrates systemic and participatory techniques to model the Russian Federation construction innovation system. Understanding this complex construction innovation system and determining the best levers for enhancing it require the dynamic modelling of a number of factors, such as flows of resources [...] Read more.

This research integrates systemic and participatory techniques to model the Russian Federation construction innovation system. Understanding this complex construction innovation system and determining the best levers for enhancing it require the dynamic modelling of a number of factors, such as flows of resources and activities, policies, uncertainty and time. To build the foundations for such a dynamic model, the employed study method utilised an integrated stakeholder-based participatory approach coupled with structural analysis (MICMAC—Matrice d'Impacts Croisés Multiplication Appliquée à un Classement Cross-Impact Matrix). This method identified the key factors of the Russian Federation construction innovation system, their causal relationship (i.e., influence/dependence map) and, ultimately, a causal loop diagram. The generated model reveals pathways to improving construction innovation in the Russian Federation and underpins the future development of an operationalised system dynamics model. Full article

(This article belongs to the Special Issue The Current State-of-the-Art of System Dynamics Modelling and Simulation)

► Show Figures

Figure 1

3093 KiB

Open AccessArticle

Using Textual Data in System Dynamics Model Conceptualization

by Sibel Eker and Nici Zimmermann

Systems 2016, 4(3), 28; https://doi.org/10.3390/systems4030028 - 04 Aug 2016

Cited by 45 | Viewed by 10374

Abstract

Qualitative data is an important source of information for system dynamics modeling. It can potentially support any stage of the modeling process, yet it is mainly used in the early steps such as problem identification and model conceptualization. Existing approaches that outline a [...] Read more.

Qualitative data is an important source of information for system dynamics modeling. It can potentially support any stage of the modeling process, yet it is mainly used in the early steps such as problem identification and model conceptualization. Existing approaches that outline a systematic use of qualitative data in model conceptualization are often not adopted for reasons of time constraints resulting from an abundance of data. In this paper, we introduce an approach that synthesizes the strengths of existing methods. This alternative approach (i) is focused on causal relationships starting from the initial steps of coding; (ii) generates a generalized and simplified causal map without recording individual relationships so that time consumption can be reduced; and (iii) maintains the links from the final causal map to the data sources by using software. We demonstrate an application of this approach in a study about integrated decision making in the housing sector of the UK. Full article

(This article belongs to the Special Issue The Current State-of-the-Art of System Dynamics Modelling and Simulation)

► Show Figures

Figure 1

754 KiB

Open AccessCommunication

Foreground and Background Components in Separable Complex Systems

by Mihir Sen, Juan Carlos Jáuregui-Correa and Carlos S. López-Cajún

Systems 2016, 4(3), 27; https://doi.org/10.3390/systems4030027 - 19 Jul 2016

Cited by 1 | Viewed by 5568

Abstract

Complex systems are composed of a large number of individual components. Many of these systems are separable, i.e., they can be split into two coupled subsystems: one with foreground components and another with background components. The former leads to narrow peaks in the [...] Read more.

Complex systems are composed of a large number of individual components. Many of these systems are separable, i.e., they can be split into two coupled subsystems: one with foreground components and another with background components. The former leads to narrow peaks in the frequency spectrum of the system and the latter gives the broad-band part. There is coupling between the two subsystems, but they can be studied separately for purposes of modeling and for analysis of experimental data. Examples from the literature are given from the area of mechanical vibrations, but the approach is quite general and can be adapted to other kinds of problems. Full article

► Show Figures

Figure 1

978 KiB

Open AccessArticle

Knowledge to Manage the Knowledge Society: The Concept of Theoretical Incompleteness

by Gianfranco Minati

Systems 2016, 4(3), 26; https://doi.org/10.3390/systems4030026 - 15 Jul 2016

Cited by 15 | Viewed by 7229

Abstract

After having outlined the essential differences between non-complex systems and complex systems we briefly recall the conceptual approaches considered by the pre-complexity General Systems Theory introduced by Von Bertalanffy in 1968 and those of the science of complexity and post-Bertalanffy General Systems Theory. [...] Read more.

After having outlined the essential differences between non-complex systems and complex systems we briefly recall the conceptual approaches considered by the pre-complexity General Systems Theory introduced by Von Bertalanffy in 1968 and those of the science of complexity and post-Bertalanffy General Systems Theory. In this context, after outlining the concept of completeness, we consider cases of incompleteness in various disciplines to arrive at theoretical incompleteness. The latter is clarified through several cases of different natures and by approaches in the literature, such as logical openness, the Dynamic Usage of Models (DYSAM), and the principle of uncertainty in physics. The treatment and the contrast between completeness and incompleteness are introduced as a conceptual and cultural context, as knowledge to manage the knowledge society in analogy, for example, with the transition from the logic of certainty to that of uncertainty introduced by De Finetti. The conceptual framework of completeness is not appropriate for dealing with complexity. Conversely, the conceptual framework of incompleteness is consistent and appropriate with interdisciplinary complexity. Full article

(This article belongs to the Special Issue Second Generation General System Theory: Perspectives in Philosophy and Approaches in Complex Systems)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Systems, Volume 4, Issue 3 (September 2016) – 6 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI